Triple
T32107100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cowan–Reines neutrino experiment |
E820011
|
entity |
| Predicate | inferredQuantity |
P173571
|
FINISHED |
| Object | neutrino flux from reactor |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: neutrino flux from reactor | Statement: [Cowan–Reines neutrino experiment, inferredQuantity, neutrino flux from reactor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inferredQuantity Context triple: [Cowan–Reines neutrino experiment, inferredQuantity, neutrino flux from reactor]
-
A.
isPerceivedQuantity
Indicates that a quantity is understood, interpreted, or experienced by an observer rather than being an objective or directly measured amount.
-
B.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
C.
relatesToQuantity
Indicates a relationship where one entity is associated with, depends on, or is characterized by a specific quantity or amount.
-
D.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
E.
mainQuantity
Indicates that the associated value represents the primary or principal quantity in a given context or relationship.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3490209c881908ec0241476715f15 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b69d1844819084898edef76b7f34 |
completed | May 3, 2026, 2:44 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: May 1, 2026, 12:27 a.m.